Time Series Essentials

1 hour

8 chapters

Intermediate

In this project, we are going to understand what a Time Series is and which are its main features.

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Web Scraping with Python

3 hours

23 chapters

Intermediate

Learn to extract valuable data from websites automatically. Master techniques to gather information efficiently, enabling you to perform in-depth analysis, make data-driven decisions, and unlock new insights from the vast ocean of online information.

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Introduction to TensorFlow

3 hours

18 chapters

Advanced

Dive deep into the world of TensorFlow with our course, designed to give you a robust understanding of its core components. Begin with an exploration of tensors and the basics of TensorFlow framework. By the course's end, you'll have honed the skills to build tensor-driven systems, including crafting a basic neural network. Equip yourself with the knowledge to harness TensorFlow's full potential and set the foundation for advanced deep learning pursuits.

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Identifying Spam Emails

2 hours

11 chapters

Advanced

We are going to classify emails as spam or non-spam by analyzing the content of the emails. We will preprocess the text data using techniques like tokenization and vectorization, then apply machine learning to build and evaluate a classification model, namely Logistic Regression. By the end of the project, we aim to develop a reliable tool for identifying spam emails.

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Automating Data Collection from Web Sources

1 hour

7 chapters

Intermediate

In this project, we are going to understand how to create a simple web scraper in Python.

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Clustering Media Content

1 hour

10 chapters

Intermediate

Now we are going to understand what a cluster is and how to use it in Python. We will explore the concept of clustering, which involves grouping a set of objects in such a way that objects in the same group (or cluster) are more similar to each other than to those in other groups. Additionally, we will demonstrate how to implement clustering algorithms using Python's popular libraries, such as scikit-learn, to identify patterns and insights within your data.

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Predicting Profitable Euro-Dollar Exchange Signals

3 hours

20 chapters

Advanced

In this course, we will examine the currency exchange rate relative to the euro. Our analysis will include Exploratory Data Analysis (EDA), generating visualizations, and developing a strategy to determine opportune moments for purchasing dollars. This strategy will involve trend detection techniques and constructing moving average curves to identify potential profit opportunities.

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Getting into NumPy Basics

1 hour

7 chapters

Intermediate

In this project, we will delve into the fundamentals of NumPy, exploring its core features and uncovering the reasons behind its significant impact on scientific computing. By understanding its architecture and capabilities, we will grasp why it is considered an essential tool for data scientists, researchers, and developers working in the realm of data analysis, machine learning, and beyond.

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Linear Regression with Python

2 hours

19 chapters

Intermediate

Linear Regression is a crucial concept in predictive analytics. It is widely used by data scientists, data analytics, and statisticians as it is easy to build and interpret but powerful enough for many tasks.

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Classification with Python

4 hours

28 chapters

Intermediate

In machine learning, classification is used in predictive modeling to assign input data with a class label. Sounds difficult? Don't worry! Let's cope with this! Welcome to the ML!

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Excel Automation with Python (project)

1 hour

11 chapters

Intermediate

In this project, we will study how to create, modify, and extract data from Excel spreadsheets using Python code.

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Identifying Fake News

2 hours

9 chapters

Advanced

We are going to identify fake news by analyzing text data and determining whether articles are legitimate or deceptive. We will preprocess the text data using natural language processing techniques and apply machine learning algorithms to build and evaluate classification models. By the end of the project, we aim to develop an effective tool that can accurately distinguish between real and fake news.

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Logistic Regression Mastering

1 hour

6 chapters

Advanced

Logistic regression is a statistical method for analyzing a dataset in which there are one or more independent variables that determine an outcome. In this project, we will leverage logistic regression to classify data into two distinct categories. The process will involve data preprocessing, model training, evaluation, and tuning to achieve optimal performance.

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Computer Vision Essentials

4 hours

29 chapters

Intermediate

Comprehensive introduction to Computer Vision, focusing on machine perception and interpretation of visual data. Covers image preprocessing, feature extraction, object detection, and deep learning techniques used in modern vision systems.

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PyTorch Essentials

3 hours

20 chapters

Advanced

Learn the fundamental and advanced concepts needed to work with PyTorch efficiently. Gain a solid understanding tensors, including creation, operations, and reshaping. Explore the essentials of gradients, backpropagation, and linear regression before moving on to handling datasets. Master the skill needed build, train, and evaluate neural networks.

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